A number of measurement studies haveconvincingly demonstrated that network traffic canexhibit a noticeable self-similar nature, which has aconsiderable impact on queuing performance.However, many routing protocols developed forMANETs over the past few years have been primarilydesigned and analyzed under the assumptions of eitherCBR or Poisson traffic models, which are inherentlyunable to capture traffic self-similarity. It is crucial tore-examine the performance properties of MANETs inthe context of more realistic traffic models beforepractical implementation show their potentialperformance limitations. In an effort towards this end,this paper evaluates the performance of three well-known and widely investigated MANET routingprotocols, notably DSR, AODV and OLSR, in thepresence of the bursty self-similar traffic. Differentperformance aspects are investigated including,delivery ratio, routing overhead, throughput and end-to-end delay. Our simulation results indicate that DSRrouting protocol performs well with bursty trafficmodels compared to AODV and OLSR in terms ofdelivery ratio, throughput and end-to-end delay. Onthe other hand, OLSR performed poorly in thepresence of self-similar traffic at high mobilityespecially in terms of data packet delivery ratio,routing overhead and delay. As for AODV routingprotocol, the results show an average performance, yeta remarkably low and stable end-to-end delay.

Recent evidences show that data traffic is beingstatistically self-similar [1, 2, 3]. This implies that datatraffic will maintain bursty characteristics. A burstytraffic is a traffic that is generated randomly, with peakrates exceeding average rates by factors of eight to ten.Let,...)2,1,0:( == iXXi(1)being a stochastic process with a constant mean, finitevariance and an autocorrelation functions as in:][iXE=α (2)

)...(/11)(kmmkmmkXXmX ++=+−, k = 1, 2, 3,… (7)For each m, the aggregated time series X(m)is a wide-sense stationary process; and r(m)is the autocorrelationfunction of it. The process X is called second-orderself-similar [1, 2, 4].The degree of burstiness is measured by a parametercalled Hurst (H) Parameter, where2/1 β−=H (8)Hurst parameter is typically a function of the overallutilization of the network. The higher H is the burstieris data traffic. Hurst parameter for a statistically self-similar traffic is in the range (0.5 < H < 1).In a simulation environment, Self-similar traffic canbe produced by multiplexing ON/OFF sources thathave a fixed rate in the ON periods and ON/OFFperiod lengths that are heavy-tailed [3] (e.g. Paretotraffic).

3. Routing protocols in MANETs

Three routing protocols were studied in this paper,namely; DSR, AODV and OLSR. Below is a briefdescription of the protocols.DSR [15]: Dynamic Source Routing protocol is areactive routing protocol, which means that nodesrequest routing information only when needed. DSR isbased on source routing concept, where the senderconstructs a source route in the packet’s header. Thissource route lists all the addresses of the intermediatenodes responsible of forwarding the packet to thedestination. When a sender wants to communicate withanother node (destination), it checks its route cache tosee if there is any routing information related to thatdestination. If route cache contains no suchinformation, then the sender will initiate a routediscovery process by broadcasting a route request. Ifthe route discovery is successful, the initiating hostreceives a route reply packet listing a sequence ofnetwork hops through which it may reach the target.Nodes may reply to requests even if they are not thedestination to reduce traffic and delay. It is alsopossible that intermediate nodes which relay thepackets can overhear the routes by parsing the packetand thus learning about routes to certain destinations.802DSR also utilizes a route maintenance scheme. Thisscheme, however, uses the data link layeracknowledgments to learn of any lost links. If any lostlink was detected, a route error control packet is sent tothe originating node. Consequently, the node willremove that hop in error from the host’s route cache,and all routes that contain this hop must be truncated atthat point.AODV [11]: Ad Hoc On-Demand Distance Vectorrouting protocol uses broadcast discovery mechanism,similar to but modified of that of DSR. To ensure thatrouting information is up-to-date, a sequence number isused. The path discovery is established whenever anode wishes to communicate with another, providedthat it has no routing information of the destination inits routing table. Path discovery is initiated bybroadcasting a route request control message “RREQ”that propagates in the forward path. If a neighborknows the route to the destination, it replies with aroute reply control message “RREP” that propagatesthrough the reverse path. Otherwise, the neighbor willre-broadcast the RREQ. The process will not continueindefinitely, however, authors of the protocol proposeda mechanism known as “Expanding Ring Search” usedby Originating nodes to set limits on RREQdissemination.AODV maintains paths by using control messagescalled Hello messages, used to detect that neighborsare still in range of connectivity. If for any reason alink was lost (e.g. nodes moved away from range ofconnectivity) the node immediately engages a routemaintenance scheme by initiating route request controlmessages. The node might learn of a lost link from itsneighbors through route error control messages“RERR”. Reference [12] indicates that Hello messagesare sent on an interval of 1 second, while nodes cantolerate a loss of 2 Hello messages before declaring alost link.OLSR [10]: Optimized Link State Routing protocolis a proactive routing protocol. It performs hop-by-hoprouting, where each node uses its most recent routinginformation to route packets. Each node in thetopology selects a set of nodes from its one hopneighbors to act as Multipoint Relays “MPR’s”. Theselection is made in a way that it covers all nodes thatare two hops away (i.e. neighbors of the neighbors).This set of nodes it responsible of retransmitting OLSRcontrol messages, hence reducing number of messagesforwarded by all neighbors as in other floodingtechniques.A node senses and selects its MPR's by means ofcontrol messages called HELLO messages that are usedto ensure a bidirectional link with the neighbor.HELLO messages are emitted at a certain interval.Nodes broadcast control messages called Topologycontrol “TC”, used to declare its MPR selection. Theseare also emitted at certain intervals. Each node is setwith a certain level of “willingness”, which is ameasure of how much is the node willing to act as aMPR for neighboring nodes.

4. Simulation setup

Extensive simulations were conducted using NS-2.While the implementation of DSR and AODV routingprotocols is provided by [8], however, OLSRimplementation is provided by [17]. The simulatednetwork consisted of 50 nodes randomly scattered in a300x600m area at the beginning of the simulation. Thetool setdest [14] was used to produce mobilityscenarios, where nodes are moving at six differentuniform speeds ranging between 0 to 20 m/s with amargin of ±1 and a uniform pause time of 10s [4, 9].We simulated the steady-state conditions of thenetwork with three types of traffic models; namelyCBR, Pareto and Exponential [4, 5, 6]. These weregenerated using the tool cbrgen.tcl [14], with thefollowing parameters:CBR: Constant Bit Rate traffic model. This wasgenerated at a deterministic rate with somerandomizing dither enabled on the interpacketdeparture interval. Packets size was set to 64 bytesgenerated at a constant rate of 2 kb/s. The packetinterarrival time is 600ms and the holding time of themodel follows a Pareto distribution with a mean of300s and a shape parameter of 2.5.Exponential: The exponential traffic model is anON/OFF model with an exponential distribution.During ON period, the traffic is generated at 2 kb/s.Average ON, OFF periods are 315ms and 325msrespectively. The holding time follows an exponentialdistribution with a mean of 300s.Pareto: The Pareto model is also composed ofON/OFF periods. However, these periods follow aPareto distribution, where traffic is generated at 2 kb/sduring ON periods. Average ON, OFF periods are315ms and 325ms respectively. The holding timefollows a Pareto distribution with a mean of 300s and ashape parameter of 2.5.It must be noted, however, that the packettransmission starts 1000 seconds after nodes start tomove to reduce the variability in the simulation results[4, 6]. The traffic models generator was properlyseeded to generate around 30 source connections,which will aggregate more data traffic towards the endof simulation causing a burstier traffic to occur. Hence,self-similarity can be achieved.For each speed with a certain traffic model, 10simulation runs were conducted to achieve higherconfidence in the obtained results. Table 1 summarizes803the simulated network area topology and mobilityparameters, while Table 2 summarizes the data trafficscenarios used in the simulation.

In this paper we have considered several metrics inanalyzing the performance of routing protocols. Thesemetrics are as follows.•Data packet delivery ratio: Total number ofdelivered data packets divided by total number ofdata packets transmitted by all nodes. Thisperformance metric will give us an idea of how wellthe protocol is performing in terms of packetdelivery at different speeds using different trafficmodels.•Normalized Protocol Overhead: Total number ofrouting packets divided by total number of delivereddata packets. Here, we analyze the average numberof routing packets required to deliver a single datapacket. This metric gives an idea of the extrabandwidth consumed by overhead to deliver datatraffic.

*Percentage of the simulation area covered by a node’s transmissionrange•Normalized Protocol Overhead (bytes): Totalnumber of routing packets (in bytes) divided by totalnumber of delivered data packets. Here, we analyzethe average number of routing packets in bytesneeded to deliver a single data packet. This is neededbecause the size of routing packets may vary.•Throughput (messages/second): Total number ofdelivered data packets divided by the total durationof simulation time. We analyze the throughput of theprotocol in terms of number of messages deliveredper one second.•Average End-to-End delay (seconds): The averagetime it takes a data packet to reach the destination.This metric is calculated by subtracting “time atwhich first packet was transmitted by source” from“time at which first data packet arrived todestination”. This includes all possible delays causedby buffering during route discovery latency, queuingat the interface queue, retransmission delays at theMAC, propagation and transfer times [16]. Thismetric is crucial in understanding the delayintroduced by path discovery.The simulation traces were analyzed, the followingare the observations noted.Data packet delivery ratio:Figure 1 shows Datapacket delivery ratio versus speed for the studiedprotocols. It is clear that packet delivery ratio is veryclose to 1 at speed 0 m/s for all protocols. However, asspeed increases, the ratio decreases dramatically.It was observed that the data packet delivery ratiosof AODV and OLSR were close to each otherthroughout the six speeds with a relatively higher ratioexhibited by AODV. Compared to the other twoprotocols, DSR has maintained good deliveryperformance when mobile nodes are moving at speedsless than 10 m/s. However, the performance degradedas speed exceeds 10 m/s reaching 0.4 for Pareto trafficat speed 20 m/s. The performance achieved by DSR isdue to the use of data link acknowledgments whichenable the mobile nodes to learn quickly about any lostlinks immediately and act accordingly. In addition, theoverhearing property allows intermediate nodes tolearn about routes to destinations, hence caching theseroutes for future use.On the other hand, the presence of Pareto trafficmodel does not exhibit any major difference in termsof packet delivery ratio compared to Exponential orCBR traffic models.Normalized Protocol Overhead:Figure 2 shows therouting overhead required to deliver a single datapacket versus speed. OLSR exhibited the highestoverhead compared to the other protocols. This isexpected since OLSR is a proactive protocol, whichrequires sending periodic HELLO and TC messages.OLSR routing overhead continues to increase804dramatically beyond the speed 1 m/s reaching 73routing packets per a single data packet for the CBRtraffic at the speed 20 m/s.On the other hand, DSR maintained the lowestrouting overhead at speeds below 10 m/s. However, therouting overhead increases dramatically after the speed10 m/s. It was observed that at speed 15 m/s, DSRproduces higher overhead than AODV. The reasonbehind this dramatic increase is that the route cacheproperty is useless when mobile nodes are moving athigher speeds and links are lost more frequently.Consequently, intermediate mobile nodes need to keepon engaging path discovery, which causes the dramaticincrease in routing overhead.AODV has maintained a remarkably low and stableoverhead throughout the six speeds. The stability innumber of routing packets per data packet was due tothat fact that AODV engages a Path Discovery onlywhen necessary. Necessity is determined by the use ofHello messages that allow nodes to learn of any lostlink and immediately inform all active nodes on thatpath.On the overall, the routing overhead in the threeprotocols was the lowest in the presence of Paretotraffic model. This was observed in the three protocols,but can be clearly identified in OLSR.Normalized Protocol overhead (bytes):Figure 3shows the routing overhead in bytes required to delivera single data packet versus speed. Similar observationswere noted as in figure 2. It is apparent that OLSRrequired almost 9000 bytes of routing packets todeliver a single data packet when using CBR traffic atthe speed of 20 m/s.

Figure 1. Data packet delivery ratio vs. speedThroughput (messages/second): Figure 4 shows thethroughput of the protocols measured inmessages/second versus speed. DSR has maintained ahigh throughput at speeds less than 10 m/s. Once againthis was due to the use of route cache and overhearingproperties of DSR routing protocol.On the other hand, the throughput observed whenusing the Pareto traffic model was higher than of thatin the case of CBR and Exponential traffic models.Average End-to-End delay: Figure 5 illustrates end-to-end delay versus speed. AODV has remarkablymaintained a low end-to-end delay throughout the sixspeeds, with a slight increase in delay at speed 20 m/s.This is because AODV can immediately use anyrouting information that it receives from intermediatenodes and it can update that information with a betterone if received later. DSR has maintained a low delayas well for speeds less than 10 m/s. However, adramatic increase in delay was observed at higherspeeds. As for OLSR routing protocol, the delay washigher compared to AODV and DSR. The reason isthat at high mobility, a MPR might move away fromthe connectivity range and a link to a currently usedpath to destination might be lost. Hence, the process ofselecting a replacement MPR and determining a newpath to destination introduces a significant amount ofdelay that severely affects the performance of theOLSR protocol.It was observed that at higher speeds, the presenceof Pareto traffic in the three routing protocolsintroduces a relatively higher delay compared to CBRand Exponential traffic models.

This paper resembles an effort to re-examine threepopular routing protocols in the presence ofstatistically self-similar traffic model. We haveanalyzed the performance of DSR, AODV and OLSRrouting protocols by simulation using NS-2, with nodesmoving at speeds ranging from 0 to 20 m/s. In order tomimic traffic models that are statistically self-similar, anumber of Pareto traffic connections were aggregatedyielding an ever bursty traffic model.The DSR routing protocol has exhibited superiorperformance in terms of data packet delivery ratio,throughput and end-to-end delay at speeds less than 10m/s compared to AODV and OLSR. On the other hand,OLSR performed poorly in the presence of astatistically self-similar traffic at high mobilityespecially in terms of data packet delivery ratio,overhead and delay. As for AODV routing protocols,the results show an average performance, yet a notablystable and low end-to-end delay was observed.As a continuation of this research work, it would bevery interesting to evaluate other protocols that havebeen suggested for important operations in MANETssuch as those for performing multicast and broadcastcommunication.

Acknowledgment

The authors would like to thank Francisco J. Rosand Pedro M. Ruiz for their help and support in theimplementation of OLSR routing protocol for the NS-2environment.